Many NP-hard problems can be formulated as sequential decision making tasks on graphs due to their highly structured nature.
Towards a controlled study of neural combinatorial optimization, we unify recent ideas [1]}, [2]}, [3]}, [4]} via a five stage end-to-end pipeline illustrated in Figure REF .
Our discussion focuses on the Travelling Salesman Problem (TSP), but the pipeline presented is generic and can be extended to characterize modern architectures for several NP-hard graph problems.
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